Presently there is a need for content classification systems that accurately reflect characteristics of the content useful to for enabling consumers to make selections. Current systems lack the capability to provide multi-dimensional classification without extensive manual processing.
Current content recommendation systems typically rely on similarity between users and/or content items as manifested in patterns of consumption and rating. Such approaches achieve reasonable results in certain environments but suffer from limitations.